You will get a Machine Learning pipeline custom-designed for your problem
Project details
You will get state-of-the-art Machine Learning and/or Deep Learning pipeline for desktop application, browser-based or mobile-based model deployment. Whether the problem is regarding Computer Vision, Natural Language Processing or Time Series data analysis and prediction I will help you add value to your projects and provide the finishing touch that will shape them into a reliable and trustworthy products. I have been delivering products for clients that yield awesome results, feel free to drop in a message for yours!
What's included
| Service Tiers |
Starter
$150
|
Standard
$230
|
Advanced
$380
|
|---|---|---|---|
| Delivery Time | 3 days | 5 days | 8 days |
Number of Revisions | 2 | 4 | 7 |
Number of Model Variations | 2 | 3 | 4 |
Number of Scenarios | 1 | 2 | 4 |
Number of Graphs/Charts | 2 | 4 | 8 |
Model Validation/Testing | |||
Model Documentation | |||
Data Source Connectivity | - | - | |
Source Code | - |
Optional add-ons
You can add these on the next page.
Fast Delivery
+$20 - $45
Additional Revision
+$10
Additional Model Variation
(+ 1 Day)
+$15
Additional Scenario
(+ 1 Day)
+$25
Additional Graph/Chart
+$10
Data Source Connectivity
(+ 1 Day)
+$35
Source Code
+$40Frequently asked questions
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SR
Sona R.
Apr 20, 2026
Computer Vision Engineer for Custom Face Parsing Segmentation Model
Working with this freelancer was an outstanding experience from start to finish. Beyond strong technical expertise, Uzair brought a level of ownership and initiative that’s rare to find. Communication was always clear, timely, and thoughtful, which made collaboration smooth and stress-free. Highly responsive to feedback, open to iteration, and consistently pushed the quality of the work forward. What really stood out was the ability to go beyond the original scope and deliver a complete, deployment-ready pipeline, saving us significant time and effort on our side. I would not hesitate to work with him again and highly recommend him to anyone looking for both technical depth and reliability. Thanks
AG
Agmk G.
May 20, 2025
ML/Al assited object detection
A sincere and competent expert. He delivered the task as intended and enjoyed working with him. Highly recommended.
GM
Glenn M.
Feb 19, 2025
Develop Video Streaming Measurement POC
RR
Roman R.
Nov 18, 2024
30 minute consultation
EK
Elias K.
May 27, 2024
30 minute consultation
About Uzair
AI Engineer -- Computer Vision | LLMs | Agents | End-End ML Systems
100%
Job Success
Rawalpindi, Pakistan - 9:05 pm local time
What separates my work from most ML engineers: I do not stop at the model. I build the APIs, the backend infrastructure, the mobile integrations, and the edge deployment pipelines that make AI actually run in production — on constrained hardware, at scale, without cloud dependency.
If you need it to work in the real world, not just in a notebook — that is what I do.
✅ What I Offer:
🔹 End-to-End AI System Development
From model design to full production deployment — APIs, backend systems, mobile integration, and edge-ready pipelines
🔹 LLMs, Generative AI & RAG Systems
Fine-tuning (LoRA, QLoRA, SFT, DPO), agentic workflows, RAG pipelines, multilingual AI, and voice-based intelligent agents
🔹 Computer Vision & Document AI
Facial recognition, liveness detection, passport validation, MRZ extraction, OCR (including low-resource languages), ICAO-compliant processing
🔹 Deepfake Detection & Fraud Prevention
Production-grade anti-spoofing systems with ultra-low false accept rates for secure eKYC and identity verification
🔹 AI for Fintech & eKYC Solutions
Complete onboarding pipelines used by banks — document verification, facial matching, fraud detection, and compliance-ready systems
🔹 Data Annotation & Dataset Engineering
High-quality image and video annotation (bounding boxes, segmentation, keypoints, tracking)
Custom dataset creation, cleaning, and labeling pipelines optimized for model performance
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🎯PRODUCTION METRICS — LIVE SYSTEMS
Every number below is from a system running in production right now:
🔹 RAG-based voice agent: under 5 sec end-to-end latency | Precision@K above 98%
🔹 Gen AI transliteration agent: under 1% Word Error Rate
🔹 Facial Recognition system: under 1% FRR | Deployed on CPU at scale with less than 5 sec latency
🔹 Document & passport validation: under 1% false rejection rate
🔹 Deepfake detection: 0.3% false accept rate | zero fakes pass | beats published SOTA
🔹 Custom OCR (Urdu & low-resource): under 1% Word Error Rate
🔹 ICAO background removal: production-certified | live in eKYC flows
These are not benchmarks. These are live metrics on systems processing real user data at this moment.
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✅ CORE EXPERTISE
🔹 LLM Fine-tuning & Generative AI
I fine-tune Llama and GPT-family models for domain-specific tasks — transliteration, document-grounded generation, structured extraction. Full pipeline: LoRA, QLoRA, SFT, and DPO alignment.
🔹 Computer Vision & Document AI
Passport validation, CNIC processing, MRZ extraction, ICAO-compliant background removal, facial comparison, occlusion detection, and liveness verification. My masked facial recognition system using diffusion models was developed as graduate thesis research.
🔹 Deepfake & Fraud Detection
Deployed deepfake detection that surpasses current published SOTA — 0.3% false-accept rate, zero fake approvals in production. One of the most reliable anti-spoofing systems in active eKYC deployment today.
🔹 AI Agents & RAG Systems
Production-grade agentic pipelines — RAG-based voice agents, tool-calling systems, multi-step reasoning workflows. Sub-5-second latency, Precision@K above 98%, running live.
🔹 eKYC & Fintech AI Infrastructure
End-to-end AI backbone for digital onboarding systems trusted by 40+ banks — decency verification, facial liveness, document fraud detection, multilingual OCR.
From Model to Production — APIs, Mobile & Edge
This is where most ML engineers stop. I do not. I build:
🔹 Scalable REST APIs and ML serving pipelines (Python, FastAPI, chi, Golang)
🔹 Concurrent, high-throughput backend systems in Golang for low-resource and CPU-only environments
🔹 Android mobile applications in Kotlin with on-device ML integration
🔹 Edge deployment pipelines — quantized, optimized models running on CPU at scale in production
If a model needs to run on a bank's on-premise server, a mobile device, or an edge node with no GPU — I have already done it.
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✅ TECHNOLOGIES
🔹 Vision: YOLOv8/v9, DeepLabV3+, Segformer, ViT, Swin Transformer, OpenCV, MediaPipe
🔹 LLMs & NLP: Llama 3.x, GPT-4, BERT, HuggingFace Transformers, LangChain, PEFT (LoRA/QLoRA)
🔹 ML Frameworks: PyTorch, TensorFlow, Keras, MMDetection, MMSegmentation
🔹 Backend: Python, Golang, FastAPI, REST APIs, concurrent systems
🔹 Mobile: Kotlin, Android, Jetpack Compose, on-device ML
🔹 Deployment: Docker, edge deployment, CPU inference, Streamlit, Colab
🔹 Data & Infra: NumPy, Pandas, Scikit-learn, Matplotlib
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🎙️LET'S TALK
If you are building an AI solution that is scalable to a wider audience, I can add serious value to the end product. Feel free to drop a message
Steps for completing your project
After purchasing the project, send requirements so Uzair can start the project.
Delivery time starts when Uzair receives requirements from you.
Uzair works on your project following the steps below.
Revisions may occur after the delivery date.
Project progress
This will demonstrate the progress that have been done so far (Premium package includes explanation over the call)
Pipeline description
This involves the technique selected and being used for the problem in hand